03428452
 Laila Saadatifard
update the ivote ...
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# include <iostream>
# include <cuda.h>
#include <stim/cuda/cudatools.h>
#include <stim/cuda/sharedmem.cuh>
#include <stim/visualization/aabb2.h>
#include <stim/visualization/colormap.h>
#include <math.h>
namespace stim{
namespace cuda{
// this kernel calculates the vote value by adding up the gradient magnitudes of every voter that this pixel is located in their voting area
template<typename T>
__global__ void cuda_vote(T* gpuVote, T* gpuGrad, T* gpuTable, T phi, int rmax, int x, int y){
extern __shared__ T S[];
T* shared_atan = S;
size_t n_table = (rmax * 2 + 1) * (rmax * 2 + 1);
stim::cuda::threadedMemcpy((char*)shared_atan, (char*)gpuTable, sizeof(T) * n_table, threadIdx.x, blockDim.x);
// calculate the 2D coordinates for this current thread.
int xi = blockIdx.x * blockDim.x + threadIdx.x;
int yi = blockIdx.y * blockDim.y + threadIdx.y;
if(xi >= x || yi >= y) return;
// convert 2D coordinates to 1D
int i = yi * x + xi;
// calculate the voting direction based on the grtadient direction
float theta = gpuGrad[2*i];
//calculate the amount of vote for the voter
float mag = gpuGrad[2*i + 1];
stim::aabb2<int> bb(xi, yi); //initialize a bounding box at the current point
bb.insert(xi + ceil(rmax * cos(theta)), ceil(yi + rmax * sin(theta)));
bb.insert(xi + ceil(rmax * cos(theta - phi)), yi + ceil(rmax * sin(theta - phi))); //insert one corner of the triangle into the bounding box
bb.insert(xi + ceil(rmax * cos(theta + phi)), yi + ceil(rmax * sin(theta + phi))); //insert the final corner into the bounding box
// compute the size of window which will be checked for finding the proper voters for this pixel
int x_table = 2*rmax +1;
int rmax_sq = rmax * rmax;
int lut_i;
T dx_sq, dy_sq;
bb.trim_low(0, 0); //make sure the bounding box doesn't go outside the image
bb.trim_high(x-1, y-1);
int by, bx;
int dx, dy;
unsigned int ind_g; //initialize the maximum vote value to zero
T alpha;
for(by = bb.low[1]; by <= bb.high[1]; by++){ //for each element in the bounding box
dy = by - yi; //calculate the y coordinate of the current point relative to yi
dy_sq = dy * dy;
for(bx = bb.low[0]; bx <= bb.high[0]; bx++){
dx = bx - xi;
dx_sq = dx * dx;
lut_i = (rmax - dy) * x_table + rmax - dx;
alpha = shared_atan[lut_i];
if(dx_sq + dy_sq < rmax_sq && abs(alpha - theta) < phi){
ind_g = (by)*x + (bx);
atomicAdd(&gpuVote[ind_g], mag);
}
}
}
}
template<typename T>
void gpu_vote(T* gpuVote, T* gpuGrad, T* gpuTable, T phi, unsigned int rmax, unsigned int x, unsigned int y){
unsigned int max_threads = stim::maxThreadsPerBlock();
dim3 threads( sqrt(max_threads), sqrt(max_threads) );
dim3 blocks(x/threads.x + 1, y/threads.y + 1);
size_t table_bytes = sizeof(T) * (rmax * 2 + 1) * (rmax * 2 + 1);
size_t shared_mem_req = table_bytes;// + template_bytes;
std::cout<<"Shared Memory required: "<<shared_mem_req<<std::endl;
size_t shared_mem = stim::sharedMemPerBlock();
if(shared_mem_req > shared_mem){
std::cout<<"Error: insufficient shared memory for this implementation of cuda_update_dir()."<<std::endl;
exit(1);
}
//call the kernel to do the voting
cuda_vote <<< blocks, threads, shared_mem_req>>>(gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
}
template<typename T>
void cpu_vote(T* cpuVote, T* cpuGrad,T* cpuTable, T phi, unsigned int rmax, unsigned int x, unsigned int y){
//calculate the number of bytes in the array
unsigned int bytes = x * y * sizeof(T);
//calculate the number of bytes in the atan2 table
unsigned int bytes_table = (2*rmax+1) * (2*rmax+1) * sizeof(T);
//allocate space on the GPU for the Vote Image
T* gpuVote;
cudaMalloc(&gpuVote, bytes);
//allocate space on the GPU for the input Gradient image
T* gpuGrad;
HANDLE_ERROR(cudaMalloc(&gpuGrad, bytes*2));
//copy the Gradient Magnitude data to the GPU
HANDLE_ERROR(cudaMemcpy(gpuGrad, cpuGrad, bytes*2, cudaMemcpyHostToDevice));
//allocate space on the GPU for the atan2 table
T* gpuTable;
HANDLE_ERROR(cudaMalloc(&gpuTable, bytes_table));
//copy the atan2 values to the GPU
HANDLE_ERROR(cudaMemcpy(gpuTable, cpuTable, bytes_table, cudaMemcpyHostToDevice));
//call the GPU version of the vote calculation function
gpu_vote<T>(gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
//copy the Vote Data back to the CPU
cudaMemcpy(cpuVote, gpuVote, bytes, cudaMemcpyDeviceToHost) ;
//free allocated memory
cudaFree(gpuTable);
cudaFree(gpuVote);
cudaFree(gpuGrad);
}
}
}
#endif
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